Axial dynamic characteristic parameters identification of rolling joints in a ball screw feed drive system. (August 2016)

• Record Type: Journal Article
• Authors: Zhu, Jianmin; Zhang, Tongchao; Wang, Jian; Li, Xiaoru
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 230:Number 14(2016)
• Page Start: 2449
• Page End: 2462
• Publication Date: 2016-08
• Subjects: Ball screw feed drive system -- mechanical joints -- dynamic characteristic parameter identification -- mechanical vibration -- genetic algorithm; Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1177/0954406215597955
• Languages: English
• ISSNs: 0954-4062

Abstract

The dynamic characteristic parameters of mechanical joints are difficult to determine in theoretical modeling, dynamic simulation, and servo controller design for the ball screw feed drive system. Therefore, this study proposes a novel method for identifying the axial stiffness and damping parameters of the rolling joints in an assembled ball screw feed drive system. First, the proposed method deduces the axial vibration equations of the feed drive system with a harmonic excitation force exerted on its worktable. Second, the identification model of the axial stiffness and damping parameters of the rolling joints is established on the basis of the equations. Third, the identification equations are built by measuring the distance between the screw supporting points, the frequency, and the amplitude of the harmonic excitation force, as well as the amplitude of the axial vibration velocity of the screw end section. The axial stiffness and damping parameters of the rolling joints are finally determined by solving the identification equations using the genetic algorithm. With a ball screw feed drive system as the research object, the proposed method is used to identify the rolling joints' axial stiffness and damping parameters of the ball screw assembly, as well as the left and the right bearing groups. The experiments show that the proposed method is correct, effective, and achieves high identification accuracy.